Where the model has them
The model has Como finishing 3rd in Serie A, with an expected finishing position of 4.1. The chances of them winning the title sit at 10.06%, whilst a top-four finish is 61.71%. Relegation is a non-issue at 0.00%. The expected points tally is 70.0. This projection is driven by a strong attack multiplier of 1.31, which is above the league average of 1.00. Their defence multiplier is 0.73, below the league average of 1.00, showing a solid defensive unit. The attacking Elo is 1646, and the defensive Elo is 1722, both contributing to the strong projected finish.
In attack
Como's attack is rated above average with a strength multiplier of 1.31. Key to this is Anastasios Douvikas, who scored 14 goals in 38 appearances last season, contributing to 32% of the team's goals. Nico Paz was the shot creator with 86 shots in 35 appearances, playing in 91% of games. Paz also chipped in with 12 goals and 6 assists. Martin Baturina added 6 goals and 3 assists. The attacking Elo of 1646 reflects this potent attacking lineup.
In defence
Defensively, Como holds a multiplier of 0.73, indicating a robust backline. The defensive-actions leaders include Andrés Cuenca with 3.98 tackles, interceptions, and blocks per 90 minutes, Alieu Fadera with 3.95, and Adrian Lahdo with 3.88. This defensive solidity is reflected in the defensive Elo of 1722, which is higher than their attacking Elo, showing a well-rounded team.
What the window changed
The transfer window saw minor adjustments to Como's attack and defence. The attack multiplier moved from 1.28 to 1.31 with the arrival of Ivan Azón, who scored 5 goals last season. The defence multiplier shifted from 0.71 to 0.73 following the addition of Luis Milla, who contributed 108 defensive actions. The departure of Mërgim Vojvoda (2 goals) and Diego Carlos had less impact on the model's projections.
Weaknesses and risks
The model sees no significant weaknesses in Como's setup. The balanced attack and defence, coupled with key player contributions and solid transfer activity, position them strongly for the upcoming season. The main risk to the projection would be underperformance from key players or injuries, but the current data doesn't flag any specific weaknesses.
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Key players (last season)
| Category | Player | Total | Per game | 1+ rate |
|---|---|---|---|---|
| Goals | Anastasios Douvikas | 14 | 0.37 | 32% |
| Assists | Adrian Lahdo | 3 | 0.33 | 33% |
| Shots | Nico Paz | 86 | 2.46 | 91% |
| Tackles won | Andrés Cuenca | 20 | 2.5 | 88% |
| Fouls drawn | Assane Diao | 39 | 2.29 | 88% |
| Fouls committed | Alieu Fadera | 36 | 1.29 | 82% |
Defensive-actions leaders (per 90)
| Player | Tackles+Int+Blocks /90 | Apps |
|---|---|---|
| Andrés Cuenca | 3.98 | 8 |
| Alieu Fadera | 3.95 | 28 |
| Adrian Lahdo | 3.88 | 9 |
Transfer impact (model)
- Attack: in Ivan Azón (5g), out Mërgim Vojvoda (2g)
- Defence: in Luis Milla (108 def actions), out Diego Carlos
_Model profile generated from the BetSignals season simulation. Player figures are last season's totals._